Establishing Methods to Monitor Influenza (A)H5N1 Virus in Dairy Cattle Milk, Massachusetts, USA

Highly pathogenic avian influenza A(H5N1) virus has caused a multistate outbreak among US dairy cattle, spreading across 16 states and infecting hundreds of herds since its onset. We rapidly developed and optimized PCR-based detection assays and sequencing protocols to support H5N1 molecular surveillance. Using 214 retail milk samples from 20 states for methods development, we found that H5N1 virus concentrations by digital PCR strongly correlated with quantitative PCR cycle threshold values; digital PCR exhibited greater sensitivity. Metagenomic sequencing after hybrid selection was best for higher concentration samples, whereas amplicon sequencing performed best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to perform monthly testing of bulk milk samples from all dairy cattle farms in Massachusetts, USA, which remain negative to date. The methods, workflow, and recommendations described provide a framework for others aiming to conduct H5N1 surveillance efforts.

Authors

Publication Details

Journal
Emerging infectious diseases
Published
2025-03-28
DOI
https://doi.org/10.3201/eid3113.250087
Citations
8
Primary Topic
Microbial infections and disease research
Type
article
Field-Weighted Citation Impact
9.46
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article

Establishing Methods to Monitor Influenza (A)H5N1 Virus in Dairy Cattle Milk, Massachusetts, USA

Katelyn S. Messer, William C. Vuyk, Catherine Brown, Tessa M. Hill et al.
8 citations
Emerging infectious diseases
Microbial infections and disease research
9.46
article

Establishing Methods to Monitor Influenza (A)H5N1 Virus in Dairy Cattle Milk, Massachusetts, USA

Katelyn S. Messer, William C. Vuyk, Catherine Brown, Tessa M. Hill, S.T. Hill, Andreas Gnirke, Michael R. Gomez, David H. O’Connor, Jon Arizti-Sanz, Pardis C. Sabeti, Nicole C. Rockey, Bronwyn MacInnis, Sami Khoury, Shirlee Wohl, Lawrence C. Madoff, Matthew K. Schnizlein, Elizabeth Curtis, Heide Knöll, Michael Mina, Al Ozonoff, Elyse Stachler, Liam Stenson, Louisa O’Connor, Daniel J. Park, Kyle McMahon, Fatinah Albeez, Pedram Samani, Natalia Wewior, Zachariah Broemmel, Charelisse Guevara-Reyes
article en
8 citations

Abstract

Highly pathogenic avian influenza A(H5N1) virus has caused a multistate outbreak among US dairy cattle, spreading across 16 states and infecting hundreds of herds since its onset. We rapidly developed and optimized PCR-based detection assays and sequencing protocols to support H5N1 molecular surveillance. Using 214 retail milk samples from 20 states for methods development, we found that H5N1 virus concentrations by digital PCR strongly correlated with quantitative PCR cycle threshold values; digital PCR exhibited greater sensitivity. Metagenomic sequencing after hybrid selection was best for higher concentration samples, whereas amplicon sequencing performed best for lower concentrations. By establishing these methods, we were able to support the creation of a statewide surveillance program to perform monthly testing of bulk milk samples from all dairy cattle farms in Massachusetts, USA, which remain negative to date. The methods, workflow, and recommendations described provide a framework for others aiming to conduct H5N1 surveillance efforts.

Emerging infectious diseasesVol. 31(13)
Zero hunger
Openalex Percentile: Top 2%
Microbial infections and disease research
9.46
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